Hyperactivity Disorder: Associations With Stimulant Treatment

Emergency Department Use and Costs for Youth With Attention-Deficit/Hyperactivity Disorder: Associations With Stimulant Treatment Cynthia L. Leibson, PhD; William J. Barbaresi, MD; Jeanine Ransom, BA; Robert C. Colligan, PhD; Jason Kemner, MPH; Amy L. Weaver, MS; Slavica K. Katusic, MD Objective.–To investigate whether, among youth with attentiondeficit/hyperactivity disorder (ADHD), stimulant treatment is associated with reduced emergency department (ED) use and medical costs. Methods.–We previously reviewed the complete and detailed school and medical records of all individuals born 1976 –1982 in Rochester, Minn, to identify those who met criteria for ADHD between age 5 years and emigration from the area. Stimulant treatment (all start/stop dates, dosages) was also abstracted. This study followed birth cohort members with ADHD in providerlinked billing data from January 1, 1987 (billing data first available), to age 18 for outcomes: ED visits, ED costs, and medical costs. For each outcome, we analyzed associations with 1) any stimulants (yes/no), 2) proportion of follow-up time on stimulants, and 3) among those treated with stimulants, periods on versus off stimulants. Results.–Of 313 youth with ADHD, 231 (74%) received any

stimulants; treatment duration ranged from 14 days to 11.8 years. Treated and untreated youth were similar with respect to median annual ED visits (0.5 vs 0.5) and medical costs ($661 vs $741) (P ⬎ .05); however, increasing proportion of follow-up on stimulants was associated with fewer ED visits (P⫽ .02) and higher medical costs (P⬍ .001). The 231 treated youth experienced an average of 3.7 periods on and off stimulants; while receiving stimulants, they exhibited fewer ED visits (P⫽ .02), lower ED costs (P ⫽ .03), and higher medical costs (P⬍ .001) compared with periods off stimulants. Conclusions.–Among youth with ADHD, extended stimulant treatment is associated with decreased ED visits and ED costs, but higher total medical costs.

Y

creases in the use of ADHD-related medication,17 and ADHD is a relatively common condition in childhood. Thus, whether ADHD-related medication is cost-saving is an important question.18 Of the very few investigations of the source of excess medical costs observed for youth with ADHD, most found that stimulant medication and associated office visits account for much of the excess costs,8 –10 and that youth who were treated with stimulant medication had higher ED costs than those not treated.8 However, interpretation of these findings is variously limited by small sample sizes; short periods of follow-up; or reliance on billing and pharmacy data to identify ADHD, with a potential bias toward high-cost treated cases.18 The present study attempts to address these limitations. It takes advantage of the fact that the complete school and medical records of 5718 members of a population-based birth cohort were previously reviewed from age 5 years to emigration from the area to identify those youth who met research criteria for ADHD (Table 1).19,20 The record review also provided information on dates, types, and dosages of ADHD-related medication prescribed to birth cohort members.21 In a previous study that used providerlinked medical billing data available for all members of the birth cohort, we demonstrated that youth who met research criteria for ADHD had markedly higher rates of

KEY WORDS: attention-deficit/hyperactivity disorder; emergency department; stimulant treatment Ambulatory Pediatrics 2006;6:45–53

outh with attention-deficit/hyperactivity disorder (ADHD) have direct medical care costs approximately double those of their unaffected peers; they are at increased risk of accidents and severe injuries and experience more frequent emergency department (ED) visits.1–13 Treatment with stimulant medication effectively reduces the core symptoms of ADHD, such as inattention and hyperactivity, and there is evidence that such treatment may also reduce the likelihood of accidents.14 –16 Therefore, it might be hypothesized that among youth with ADHD, treatment with stimulant medication would also contribute to reductions in ED use and medical costs. Recent decades have been characterized by dramatic inFrom the Departments of Health Sciences Research (Drs Leibson and Katusic, Ms Ransom, and Ms Weaver), Pediatric and Adolescent Medicine (Dr Barbaresi), and Psychiatry and Psychology (Dr Colligan), Mayo Clinic College of Medicine, Rochester, Minn; and McNeil Consumer & Specialty Pharmaceuticals, Fort Washington, Pa (Mr Kemner). Presented in part as a poster presentation at the Pediatric Academic Societies’ annual meeting, San Francisco, Calif, May 2004. This study was funded by McNeil Consumer & Specialty Pharmaceuticals. Mr Kemner is an employee of McNeil Consumer & Specialty Pharmaceuticals. Address correspondence to Cynthia L. Leibson, PhD, Mayo Clinic, Department of Health Sciences Research, 200 First St NW, Rochester, MN 55905. e-mail: [email protected]. Received for publication April 5, 2005; accepted August 26, 2005.

AMBULATORY PEDIATRICS Copyright © 2006 by Ambulatory Pediatric Association

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Volume 6, Number 1 January–February 2006

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Table 1. Research Criteria for Attention-Deficit/Hyperactivity Disorder (ADHD) Case Definition* Meets all DSM-IV Criteria for ADHD†

Positive ADHD Questionnaire Results

Clinically Diagnosed as ADHD

⫹ ⫹ ⫹ ⫺ ⫺

⫹ ⫹ ⫺ ⫹ ⫺

⫹ ⫺ ⫹ ⫹ ⫹

No. of Subjects 170 41 17 122 29

228 379 151

*Plus indicates the presence of a given criterion; minus, the absence of a given criterion. †The age criterion was not used; of the 151 individuals who qualified for reasons other than DSM-IV criteria, 106 had fewer than 6 separate entries of “inattentive” or “hyperactive-impulsive” symptoms, and 45 had symptoms noted by only one person and/or for less than 6 months.

medical care utilization (including ED visits) and approximately double the medical care costs compared with those without ADHD.11 The present study expands upon our previous findings to investigate whether the high rates of ED use and medical costs observed for youth with ADHD are reduced by treatment with stimulant medication. The sample is limited to members of the birth cohort who met research criteria for ADHD. The outcomes under consideration (dependent variables) include ED visits, ED costs, and total medical care costs. The exposure (independent variable) is treatment with stimulant medication, considered both as a dichotomous variable (any treatment, yes/ no) and as a continuous variable (proportion of time on treatment). Among the subset of youth with ADHD who received any stimulant treatment, we also compare the outcomes during periods on versus off stimulants. METHODS Study Setting This retrospective epidemiologic study was approved by Mayo Foundation and Olmsted Medical Center Institutional Review Boards. It was conducted in Rochester, Minn, the county seat of Olmsted County (population 124 277 [2000 census]; 90% white). With the exception of a higher proportion of persons employed in the health care sector, characteristics of Olmsted County residents are similar to those of the United States white population.22 Data Resources Data resources included the Rochester Epidemiology Project (REP) medical records linkage system, Independent School District (ISD) 535 student records, and the Olmsted County Health Care Expenditure Dataset (OCHEUD). REP Population-based epidemiologic studies are possible in this community because Rochester is geographically isolated and home to Mayo Clinic, one of the world’s largest medical centers. Olmsted County residents receive medical services primarily from Mayo Clinic and Olmsted

Medical Center (OMC), another group practice, and their affiliated hospitals. Since 1907, information from every Mayo encounter is contained within a patient-based medical record. All diagnoses and surgical procedures are indexed for automated retrieval. Under the auspices of the REP, the indexing and medical records linkage was expanded to include other local medical facilities, including OMC and the area’s few private medical practitioners. The records contain complete (hospital inpatient/outpatient, ED, physician’s office, and specialty clinic encounters) and detailed information (all clinicians’ notes, including psychiatry/psychology/neurology exams; all diagnostic and laboratory results, including surveys and questionnaires; all other results; and correspondence) from essentially all providers of medical care to local residents.22 ISD 535 Records Youth from Rochester and surrounding townships attend public, parochial, and private schools that constitute ISD 535. Through a contractual agreement, the cumulative school records of students registered at the 41 schools, including those who emigrated, died, graduated, or were home-schooled, are available for approved research. The records are complete and detailed. Of relevance to ADHD, the records contain all notes related to any difficulties in learning, performance, or behavior observed by teachers, parents, school psychologists, social workers, guidance counselors, nurses, or physicians; Individual Education Program reports; periodic Individual Education Program reviews; Individual Educational Assessment/Reassessment Report forms; referral forms; private tutoring/evaluation reports, all reports from individual or group standardized tests of ability or achievement; student progress and report cards, school nurse logs; and medication administration authorization forms.19 OCHEUD The OCHEUD contains provider-linked billing data from Mayo Clinic, Olmsted Medical Center, and affiliated hospitals. The OCHEUD affords access to virtually all sources of medical care available to and utilized by residents of Olmsted County, as evidenced by the finding that more than 95% of all hospitalizations among local Medicare-eligible residents occur at the 3 area hospitals affiliated with Mayo Clinic and OMC (1988 MEDPAR file, Health Care Financing Administration). Hospital and ambulatory care data are available in electronic format from 1987 through present and include line-item detail on date, type, frequency, and billed charge for every good or service provided. A standardized, inflation-adjusted dollar cost is assigned to each line item using a unit-costing algorithm.23 Costs for hospital-billed items are assigned by multiplying the billed charge for each item by the cost-center–specific cost-to-charge ratio for the year in which the service was delivered (as obtained from Medicare cost reports for each of the 3 hospitals). Costs for each year are expressed as 2000 national average dollars, adjusted for inflation and geography.24,25 Services billed by physicians and/or provided in nonhospital settings are

AMBULATORY PEDIATRICS

classified by using the Health Care Financing Administration Common Procedure Coding system and are costed with the code-specific 2000 Medicare national average allowed fee. Study Sample The sample for this study is a subset of a populationbased cohort of 379 youth previously identified as meeting research criteria for incident ADHD (Table 1). The 379 were identified following review of the complete school and medical records of 5718 children born 1976 –1982 to mothers residing in Rochester townships (comprising ISD 535) from age 5 forward until emigration, death, or end of the study.19,20 Because formal diagnostic criteria for ADHD are typically met after children begin school, the review was limited to individuals residing locally after age 5 years. Potential migration bias from birth to age 5 years was previously shown to be minimal.26 A detailed description of the 5-step approach for identifying ADHD is published elsewhere19 and summarized here. First, ISD 535 school records for all 5718 subjects were reviewed, page by page, for evidence of concerns about learning or behavior. Second, for all 1951 subjects so identified, school and REP medical records were reviewed for additional information, including 1) symptoms associated with ADHD, as specified in DSM-IV,27 2) teacher/parent ADHD questionnaire results, 3) clinical diagnoses of ADHD, and 4) documentation of medication treatment for ADHD. The 1171 subjects with one or more of these 4 types of information were defined as potential ADHD cases. Third, for the 3767 birth cohort members not identified as having learning or behavior concerns in step 1, the REP computerized index of medical diagnoses was searched for ADHD-related diagnosis codes. School and medical records of birth cohort members with such codes were reviewed for the 4 types of information described above, yielding 169 additional potential ADHD cases. Fourth, records of birth cohort members identified as receiving care from the non-Mayo, non-OMC provider of psychiatric care were reviewed, yielding 4 additional potential ADHD cases. In the fifth and final step, ADHD status among the 1344 potential cases was determined by applying explicit research criteria, consisting of specified combinations of the following: 1) met DSM-IV criteria for ADHD,27 2) positive results on ADHD questionnaires, and 3) clinical diagnoses of ADHD as documented in the medical record. DSM-IV exclusion criteria27 were also applied (ie, individuals with a diagnosis of pervasive developmental disorder, severe mental retardation, schizophrenia, or other psychotic disorder were excluded). Three hundred seventy-nine individuals met criteria for incident ADHD (Table 1).19,20 The sample for the present study is a subset of these 379 individuals. It was first limited to individuals who had not emigrated before January 1, 1987 (age range 5–11 years) the date OCHEUD data on cost and utilization were first available. Because local youth often leave the area after age 17 years, follow-up for the present study was censored as of the 18th birthday. To address the potential impact of

ADHD Medication and ED Use and Costs

47

loss to follow-up on stimulant treatment and medical care utilization and costs, the present study was also limited to individuals who were residing locally through age 17 years (ie, for whom we had complete follow-up data). Potential migration bias from January 1, 1987, to age 18 years was previously shown to be minimal.11 There were 319 birth cohort members with ADHD who met these residency criteria. Following identification of these individuals, a statute was instituted that required patient authorization for use of medical records for research.28 Six individuals who refused authorization were excluded from subsequent review, leaving 313 individuals for analysis. Data Collection Stimulant Treatment The exposure (independent variable) of interest for this study of youth with ADHD was stimulant medication. The study took advantage of the fact that the medical records of all birth cohort members who met research criteria for ADHD were previously reviewed for all ADHD-related pharmacological treatment (eg, stimulants, centrally acting ␣-agonists, tricyclic antidepressants) from birth forward.20,21 For each individual, we identified the date each specific medication was prescribed, at each specific dosage, and for what length of time, as documented in the medical records. The present study was limited to treatment with any stimulant medication from January 1, 1987, the date OCHEUD cost and utilization data were first available, through age 17 years. For each individual we identified whether they received any stimulants during their follow-up (yes/no). Based on start and stop dates for each individual, we calculated the number of days and proportion of their follow-up that they were on stimulants; individuals with no stimulant treatment during follow-up were assigned a value of zero. In addition, for those individuals with any stimulants, their total follow-up was divided chronologically into on- and off-treatment periods, with each period defined by the start and stop of stimulant treatment. Periods were measured in days and divided by 365.25. Medical Care Utilization and Costs The outcomes (dependent variables) of interest for this study were ED visits, ED costs, and total medical costs. Individuals were followed for these outcomes in the OCHEUD from January 1, 1987, through age 17 years. The OCHEUD does not include costs for any outpatient pharmaceuticals (eg, asthma medications, antibiotics, antidepressants, stimulant medications). For this study, we were able to estimate costs for stimulant medications by applying published estimates of cost per dose to the detailed data on stimulant dosage that were abstracted from the medical record (see above). Therefore, we calculated 2 separate estimates of total medical costs. The first excludes all medication costs. The second includes stimulant costs but no other medication costs. For the second estimate, all stimulant doses were first converted to methylphenidate equivalent units as follows: 20 mg methylphenidate ⫽ 10

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Table 2. Characteristics of Youth With Attention-Deficit/Hyperactivity Disorder (ADHD) Treated or Not Treated With Stimulants During Follow-up

Characteristic

All Youth With ADHD (N ⫽ 313)

Any Stimulants (N ⫽ 231)

No Stimulants (N ⫽ 82)

P Value*

Age, yr, mean ⫾ SD† Years of follow-up, mean ⫾ SD Male sex, n (%) Comorbid psychiatric diagnoses, n (%)

7.7 ⫾ 1.9 10.2 ⫾ 1.4 236 (75) 169 (54)

7.4 ⫾ 1.9 10.4 ⫾ 1.4 180 (78) 119 (52)

8.5 ⫾ 1.7 9.7 ⫾ 1.4 56 (68) 50 (61)

⬍.001 ⬍.001 .08 .14

*For comparisons between youth with and without stimulants. †Age as of January 1, 1987.

mg dextroamphetamine ⫽ 56.25 mg pemoline ⫽ 10 mg methamphetamine ⫽ 10 mg levoamphetamine plus dextroamphetamine combination.21 Stimulant costs were estimated by using the Federal Upper Limit for Medicaid reimbursement wholesale price for methylphenidate hydrochloride in calendar year 2000, assuming 10-mg tablets in quantities of 100.29 Costs for each individual were estimated by multiplying the published cost per milligram by their total milligrams in methylphenidate equivalent units prescribed during each period and summing over their entire follow-up. Psychiatric Comorbid Conditions The medical and school records of each youth with ADHD were reviewed by a Developmental and Behavioral pediatrician (WJB) for all psychological and psychiatric evaluations and treatment. Each individual was assigned a dichotomous variable for comorbid psychiatric diagnoses (yes/no), based on the presence of any documented clinical diagnosis within the following DSM-IV categories: disorders of conduct, mood, anxiety, eating, personality, or adjustment.30 Statistical Analysis We conducted 3 sets of analysis. In the first and second sets, all ED visits, ED costs, and total medical costs for each individual were summed over their full follow-up, divided by using their length of follow-up in days, and expressed as annual rates. The first set of analyses compared each of the outcomes between individuals with any stimulant treatment during their follow-up and individuals with no stimulant treatment by the Wilcoxon rank sum test. The second set of analyses assessed the relationship between each of the outcomes and the proportion of follow-up time on stimulants (defined above) by using generalized linear regression models. To account for skewed distributions and zero events, ED visits were transformed to the natural log of [(number of visits plus 0.5)/personyears of follow-up] and costs were transformed to the natural log of [(costs plus $1)/person-years of follow-up]. Visual inspection of histograms and normal probability plots was used to confirm that, after transformation, the outcomes were normally distributed. Each outcome was then modeled as a normally distributed variable, after applying transformations. Additional models were fit to explore these relationships, after adjusting for sex and age

as of January 1, 1987. We also adjusted for, and stratified by, the presence or absence of comorbid psychiatric diagnoses (defined above). The third set of analyses was limited to youth with any stimulant treatment during follow-up. The unit of observation was a treatment period (defined above), with each period assigned an indicator variable denoting whether an individual was on or off stimulants. Generalized linear models were used to evaluate the association between stimulant treatment (on/off) and the rate of ED visits, ED costs, and total medical costs per period. Because almost all individuals had multiple on/off periods, the withinindividual outcomes were likely to be correlated. Generalized Estimating Equation (GEE) methodology (SAS PROC GENMOD; by using an exchangeable correlation structure) was used to model the correlations and obtain appropriate robust error variances.31 ED visits, ED costs, and total medical costs were obtained for each separate period; ED visits were transformed to the natural log of [(number of visits plus 0.01)/length of period in years]; costs were transformed to the natural log of [(costs plus 1 dollar)/length of period in years]. Visual inspection of histograms and normal probability plots was used to confirm that, after transformation, the outcomes were normally distributed. Each outcome was then modeled as a normally distributed variable, after applying transformations. Additional models were fit to explore associations after adjusting for sex and both calendar year and age as of the mid-point of the period. All statistical analyses were performed by using SAS software (SAS Institute, Cary, NC). All P values were 2-sided, with P ⬍ .05 considered statistically significant. RESULTS The 313 members of the 1976 –1982 Rochester birth cohort who met research criteria for ADHD and were residing locally through age 17 years contributed 3196 years of follow-up (range 7.0 –13.0 years) from January 1, 1987 (when they were 5–11 years of age), to their 18th birthday. During this time, 231 youth (74%) received some stimulant treatment. Compared with the 82 youth with no stimulant treatment, those treated with stimulants were younger as of January 1, 1987, and thus experienced longer follow-up. The 2 groups did not differ significantly with respect to sex or presence of comorbid psychiatric diagnoses (Table 2).

AMBULATORY PEDIATRICS

ADHD Medication and ED Use and Costs

49

Table 3. Emergency Department (ED) and Medical Costs for Youth With Attention-Deficit/Hyperactivity Disorder Outcome

Any Stimulants

No Stimulants

Number ED visits/yr No. visits/yr Mean ⫾ SD Median Range ED costs/yr Mean ⫾ SD Median Range Total medical costs/yr (excluding all medication costs) Mean ⫾ SD Median Range Total medical costs/yr (including stimulant costs but no other medication costs) Mean ⫾ SD Median Range

231

82

0.60 ⫾ 0.56 0.47 0–4.0

0.76 ⫾ 0.78 0.52 0–3.8

$105 ⫾ 111 $72 $0–$799

$147 ⫾ 165 $82 $0–$921

$1,099 ⫾ 1,669 $661 $6–$16,201

$962 ⫾ 856 $741 $108–4,577

P Value*

.33

.08

.58

.21 $1,246 ⫾ 1,699 $836 $10–$16,601

$962 ⫾ 856 $741 $108–$4,577

*Wilcoxon rank sum test.

Comparisons of Outcomes Between Youth With and Without Stimulant Treatment During the 3196 person-years of follow-up, all 313 youth experienced some medical costs, and 294 (94%) had one or more ED visit. On average, ED costs accounted for 15% (SD 12, median 12%) of total medical costs per year (for the estimate that excluded all medication costs). And on average, costs for stimulant medication accounted for 13% (SD 6, median 5%) of total medical costs per year (for the estimate that included stimulant costs but no other medication costs). Compared with youth with ADHD and no stimulants, those with any stimulants had lower mean and median values for ED visits and ED costs but higher mean and median values for total costs. Tests for difference between the groups, however, did not reach statistical significance (Table 3). Associations Between Outcomes and Proportion of Follow-up on Stimulants There was marked variability among youth treated with stimulants with respect to treatment duration [range 14 days to 11.8 years, mean (SD) 3.5 (2.8) years, median 2.8 years]. Results from analyses of the association between the proportion of follow-up time on treatment (with youth with no stimulant treatment assigned a value of zero) and each of the outcomes are provided in Table 4 and summarized below. Annual ED Visits The annual rate of ED visits declined with increasing proportion of time on stimulants. The inverse association was significant in unadjusted and age- and sex-adjusted models, and remained significant when the variable for comorbid psychiatric diagnoses was added. Interestingly, there was a suggestion that the inverse association between ED visits and the proportion of time on stimulants was concentrated among the 169 youth with a comorbid

psychiatric diagnosis (P⫽ .08) rather than among the 144 youth with no comorbid psychiatric diagnosis (P⫽ .24) (Table 4). However, the test for interaction between comorbid psychiatric diagnoses and the proportion of time on stimulants failed to reach statistical significance (P⫽ .61). Annual ED Costs In unadjusted and adjusted models for ED costs in Table 4, the beta coefficients for the proportion of time on stimulants were all negative, ie, an inverse relationship. However, the relationship was not statistically significant in either model. Annual Total Medical Costs For the estimate of total medical costs that excluded all medication costs, there was no significant association with the proportion of time on stimulants, in either the unadjusted model or the age- and sex-adjusted model. However, when the variable for comorbid psychiatric diagnoses was added to the model, it contributed significantly to annual total medical costs, and the proportion of time on stimulants tended to be positively associated with annual total medical costs. When stratified by the presence of comorbid psychiatric diagnoses, there was no significant association between the proportion of time on stimulants and annual total medical costs for youth either with or without comorbid psychiatric diagnoses. The proportion of time on stimulants was associated with increased total medical costs for the estimate that included stimulant costs but no other medication costs. The association was apparent in unadjusted and adjusted models; it was also evident for youth with and without comorbid psychiatric diagnoses. Consideration of higher order terms for the proportion of time on stimulants revealed no evidence of a nonlinear association with either ED visits, ED costs, or total med-

50

Adjusted for Age and Sex

Unadjusted Characteristic

␤

SE

P Value

␤

SE

P Value

⫺.05

.02

.01

⫺.04

.02

... ... ...

... ... ...

... ... ...

⫺.01 ⫺.005 ...

⫺.06

.04

.10

... ... ...

... ... ...

.02 ... ... ...

.08 ... ... ...

Comorbid Psychiatric Diagnosis (N ⫽ 169)

No Comorbid Psychiatric Diagnosis (N ⫽ 144)

␤

SE

P Value

␤

SE

P Value

␤

SE

P Value

.02

⫺.04

.02

.02

⫺.04

.03

.08

⫺.03

.03

.24

.12 .03 ...

.93 .86 ...

⫺.01 .0002 .15

.12 .03 .11

.91 .99 .17

⫺.16 .04 ...

.16 .04 ...

.33 .37 ...

.14 ⫺.01 ...

.18 .04 ...

.43 .77 ...

⫺.06

.04

.12

⫺.06

.04

.16

⫺.09

.06

.10

⫺.01

.06

.87

... ... ...

.04 .01 ...

.27 .06 ...

.89 .86 ...

.03 .02 .31

.27 .06 .24

.90 .73 .18

⫺.32 .05 ...

.35 .08 ...

.35 .53 ...

.46 ⫺.01 ...

.42 .09 ...

.28 .88 ...

.02

.20

.03

.02

.14

.04

.02

.05

.04

.02

.10

.04

.03

.17

... ... ...

... ... ...

.04 .03 ...

.12 .03 ...

.74 .33 ...

.04 .04 .48

.12 .03 .11

.77 .11 ⬍.001

⫺.12 .08 ...

.15 .04 ...

.43 .04 ...

.20 .02 ...

.19 .04 ...

.29 .68 ...

.02

⬍.001

.09

.02

⬍.001

.10

.02

⬍.001

.09

.02

⬍.001

.11

.03

⬍.001

... ... ...

... ... ...

.04 .04 ...

.11 .03 ...

.72 .16 ...

.03 .05 .43

.11 .02 .10

.76 .04 ⬍.001

⫺.09 .08 ...

.14 .03 ...

.51 .02 ...

.18 .03 ...

.17 .04 ...

.31 .47 ...

*Defined as (natural log plus 0.05)/person-years of follow-up. †Defined as (number of days on stimulants/days of follow-up)/365.25. ‡Defined as (natural log plus 1.0)/person-years of follow-up

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ED visits/yr* Proportion of time on stimulants† Male sex Age (1987) Psychiatric diagnoses ED costs/yr Proportion of time on stimulants† Male sex Age (1987) Psychiatric diagnoses Total medical costs/yr (excluding all medication costs)‡ Proportion of time on stimulants† Male sex Age (1987) Psychiatric diagnoses Total medical costs/yr (including stimulant costs but no other medication costs)‡ Proportion of time on stimulants† Male sex Age (1987) Psychiatric diagnoses

Adjusted for Age, Sex, and Comorbid Psychiatric Diagnosis

Leibson et al

Table 4. Generalized Linear Models of the Associations Between the Proportion of Time On Stimulants and Annual Rates of Emergency Department (ED) Visits, ED Costs, and Total Medical Costs for Youth With Attention-Deficit/Hyperactivity Disorder

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Table 5. Emergency Department (ED) Visits, ED Costs, and Total Medical Costs for the 231 Youth With Attention-Deficit/Hyperactivity Disorder Who Were Treated With Stimulants at Any Time During Follow-up, Characterized as to Periods They Were On Versus Off Treatment Outcome Length of follow-up, yr Mean ⫾ SD ED visits/yr Mean ⫾ SD Median IQR† Range ED costs/yr Mean ⫾ SD Median IQR† Range Total medical costs/yr (excluding all medication costs) Mean ⫾ SD Median IQR† Range Total medical costs/yr (including stimulant costs but no other medication costs) Mean ⫾ SD Median IQR† Range

On Treatment

Off Treatment

P Value

2.5 ⫾ 2.3

4.0 ⫾ 2.4

⬍.01

0.62 ⫾ 1.42 0.16 0–0.73 0–13.04

0.67 ⫾ 0.92 0.40 0.14–0.90 0–6.2

$106 ⫾ $257 $13 $0–$114 $0–$1,978

$111 ⫾ $174 $59 $10–$140 $0–$833

$1,247 ⫾ $1,841 $643 $320–$1,528 $0–$12,468

$1,334 ⫾ $2,997 $600 $280–$1,200 $0–$28,656

⬍.02

⬍.001

⬍.001 $1,629 ⫾ $1,867 $1,072 $698–$1,876 $0–$12,728

$1,334 ⫾ $2,997 $600 $280–$1,200 $0–$28,656

*The summary statistics are based on raw (untransformed) values. P values are from unadjusted models that evaluate log-transformed outcomes using generalized estimating equations methodology. †Interquartile range, 25th and 75th percentiles.

ical costs. We also conducted analyses excluding outliers, and analyses limited to the 231 youth with any stimulants, ie, excluding the 82 youth with treatment duration equal zero. The conclusions were unchanged from those presented above (data not shown, available on request). Associations Between Outcomes and On/Off Stimulant Periods The 231 youth with ADHD who were treated with stimulants experienced a total of 853 treatment periods (370 on stimulants, 483 off stimulants). There was marked variability; 2 individuals were on stimulants during their entire follow-up; 4 individuals switched between on and off stimulants 10 times (ie, 11 periods) (mean number of periods 3.7 ⫾ median ⫽ 3). The average length of time for on periods was approximately two-thirds the average length of time for off periods (Table 5). Table 5 provides annual rates of ED visits, ED costs, and total medical costs while on versus off stimulants. The results from unadjusted models in Table 5 are consistent with results from models that adjusted for sex and both age and calendar year as of the mid-point for each treatment period. Adjusted estimates revealed significant reductions in annual rates of both ED visits (P⫽ .02) and ED costs (P⫽ .03) for on versus off stimulants. By contrast, total medical costs were significantly increased during periods of on versus off stimulants, both for the estimate that excluded all medication costs (P⬍ .001) and for the estimate that included stimulant costs but no other medication costs (P⬍ .001).

DISCUSSION This population-based study of 313 youth with research identified ADHD revealed that, as the proportion of follow-up time on stimulants increased, the number of ED visits per year decreased and total medical costs per year increased. Analyses limited to youth with ADHD who received any stimulants during the study period (N⫽231) revealed the number of ED visits per year and the ED costs per year were lower during periods they were on stimulants compared with periods they were off stimulants. However, total medical costs, both for the estimate that excluded all medication costs and for the estimate that included stimulant costs but no other medication costs, were significantly higher during periods on versus off stimulants. There are few published studies of the association between medical costs for youth with ADHD and pharmacological treatment of ADHD. A large Canadian study that assessed 7 years of pharmaceutical and billing data revealed that youth with a prescription for methylphenidate (MPH) had an approximately 2-fold increased risk of ED use and higher rates of utilization for all medical services compared with the general population of youth with no MPH prescription.3 Importantly, as recognized by the authors,3 no comparisons were available for youth with ADHD and no MPH prescription; indeed the number of youth in this classification was unknown. By using 1996 Medical Expenditure Survey data, Chan et al8 identified 165 youth with ADHD based on informant report and/or evidence of ⱖ2 prescriptions for stimulant medications.

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The 114 youth with ADHD who had a prescription for stimulant medication during the year had total, outpatient visit, and prescription costs more than double those for the 51 youth with ADHD and no prescription for stimulant medication. Although the difference in ED costs between youth with ADHD who did and did not have a prescription was not statistically significant, the mean ED costs for youth with ADHD who had a prescription for stimulant medication ($196.56) was nearly 5 times that for youth with ADHD and no such prescription ($39.95).8 It is important to note that in the study by Chan et al,8 as with most other investigations of the source of excess medical costs associated with ADHD,2,9,10 ascertainment of ADHD cases was limited to a short period of observation and based on a clinical diagnosis of ADHD and/or prescription fills for stimulant medication. Thus, costs and utilization accrued by youth with ADHD who were not yet diagnosed, or no longer being treated, were potentially misclassified as non-ADHD. The potential circularity inherent in such study designs could result in substantial underestimates of ADHD-associated ED use and overestimates of ADHD-associated stimulant treatment costs.18 This point was underscored by Swensen et al,6 who relied on administrative data for ascertaining ADHD but expanded the period of ascertainment to 3 years (1996 – 1998), while estimating outcomes for a single year (1998). Only 53% of subjects identified as having ADHD in the 3-year period received care directly for the treatment of ADHD in 1998, and 41% did not fill a prescription for ADHD-related stimulants during that year. Importantly, approximately 80% of the costs accrued by youth identified as having ADHD were not associated with ADHD diagnoses.6 The present study is unique in several respects. The sample consisted of research-identified ADHD cases drawn from a large population-based birth cohort. Data on health care utilization and costs were afforded with the line-item detail contained within provider-linked billing data for each individual and were available from January 1, 1987 (when birth cohort members ranged in age from 5–11 years), through age 17 years, for a mean follow-up of 10.2 years. The extensive follow-up provided sufficient numbers of relatively infrequent, but clinically important, events (eg, ED visits). Detailed information on treatment with stimulant medication (all start and stop dates and dosages) was obtained over the entire period of follow-up. Limitations Study limitations include that it was conducted in a single geographic setting and the sample was 95% white. The sample size was relatively small. By using the 2-sided Wilcoxon rank sum (Mann-Whitney U) test, we were unable to detect a statistically significant difference in the annual rate of ED visits between youth with ADHD who were and were not treated with stimulants at any time during follow-up (P⫽ .33). The observed probability that the annual rate of ED visits for youth with any stimulants was less than that for youth with no stimulants was 0.534. A probability of 0.604 was required in order to achieve

AMBULATORY PEDIATRICS

80% power to detect a significant difference.32 Importantly, however, our analysis of the association between annual rate of ED visits and the proportion of time on stimulants employed the same sample and yet revealed a significant inverse association (P⫽ .02). The contrasting results reflect the fact that for 25% of youth with any stimulant treatment, the proportion of follow-up on stimulants was ⬍10%. These findings suggest that it is not the characteristic of whether youth with ADHD are ever treated with stimulants but rather the duration of treatment. The latter was reinforced by our analysis limited to ADHD youth with any stimulant treatment, in which we found a significantly lower rate of ED visits during periods they were on versus off stimulants. ADHD case ascertainment was retrospective. However, the cumulative incidence of ADHD in the 1976 –1982 birth cohort20 is consistent with point prevalence estimates from population-based studies that prospectively applied DSM criteria.33–36 The validity of our case criteria was previously investigated by comparing cases who did and did not meet DSM-IV criteria (Table 1) for several characteristics (eg, sex, treatment, school outcomes, medical costs); there were no significant differences.11,19 Stimulant use was based on medical record review. Although review of school records provided some assurance that medication was actually administered during school hours, many youth with ADHD receive medication only outside the school setting. Thus, we could not definitively determine that all individuals were taking the medication. However, individuals were considered as treated with stimulants only if there was indication in the medical record that they were taking the medications or if prescription refills were written. We did not have costs for nonstimulant medications. Youth with ADHD who are treated with stimulants may be more likely to receive other medications (eg, antidepressants),6,37 and thus the observed increase in total medical costs with increasing proportion of time on stimulants may have been greater if all medication costs were included. Our observation that total medical costs for youth with ADHD were higher for those who had comorbid psychiatric diagnoses is consistent with previous studies.2,8,9 It is important to note, however, that determination of comorbid psychiatric conditions in each of these studies, including our own, was based on clinical diagnoses. Another important limitation of our study and previous studies is that treatment assignment was not random. Thus, observed associations may be confounded by differences in unmeasured characteristics (eg, symptom severity or risk-related activities). However, to the extent that youth with more severe symptoms may be more likely to both visit the ED and remain on treatment,38 such confounding would likely produce observations opposite those we observed. Clinical Implications Study findings lend support to the argument that extended stimulant treatment of youth with ADHD may reduce the frequency and costs of ED visits. Cost reductions do not appear to outweigh the costs for stimulant

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ADHD Medication and ED Use and Costs

medication and associated costs (eg, office visits for medication monitoring). ACKNOWLEDGMENTS The project was supported by research grants from the Public Health Service, National Institutes of Health (HD29745 and AR30582) and by an investigator-initiated research grant from McNeil Consumer & Specialty Pharmaceuticals. We acknowledge the contributions of Diane Siems, the study coordinator, and Candice Klein and Jeaneen Alcorn, data abstractors. We thank Karen Tennison for assistance with manuscript preparation. We also thank individuals involved with ISD 535 for their cooperation and collaboration.

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REFERENCES 1. Birnbaum HG, Kessler RC, Lowe SW, et al. Costs of attentiondeficit hyperactivity disorder (ADHD) in the US: excess costs of persons with ADHD and their family members in 2000. Curr Med Res Opin. 2005;21:195–206. 2. DeBar LL, Lynch FL, Boles M. Healthcare use by children with attention deficit/hyperactivity disorder with and without psychiatric comorbidities. J Behav Health Serv Res. 2004;31:312–323. 3. Miller AR, Brehaut JC, Raina P, et al. Use of medical services by methylphenidate-treated children in the general population. Ambul Pediatr. 2004;4:174 –180. 4. Swensen AR, Birnbaum HG, Ben Hamadi R, et al. Incidence and costs of accidents among attention-deficit/hyperactivity disorder patients. J Adolesc Health. 2004;35:346 –347. 5. Burd L, Klug MG, Coumbe MJ, Kerbeshian J. Children and adolescents with attention deficit-hyperactivity disorder: 1. Prevalence and cost of care. J Child Neurol. 2003;18:555–561. 6. Swensen AR, Birnbaum HG, Secnik K, et al. Attentiondeficit/hyperactivity disorder: increased costs for patients and their families. J Am Acad Child Adolesc Psychiatr. 2003;42:1415–1423. 7. Brehaut JC, Miller A, Raina P, McGrail KM. Childhood behavior disorders and injuries among children and youth: a population-based study. Pediatrics. 2003;111:262–268. 8. Chan E, Zhan CL, Homer CJ. Health care use and costs for children with attention-deficit/hyperactivity disorder—national estimates from the Medical Expenditure Panel survey. Arch Pediatr Adolesc Med. 2002;156:504 –511. 9. Guevara J, Lozano P, Wickizer T, et al. Utilization and cost of health care services for children with attention-deficit/hyperactivity disorder. Pediatrics. 2001;108:71–78. 10. Kelleher JK, Childs GE, Harmon JS. Healthcare costs for children with attention-deficit/hyperactivity disorder. Econ Neurosc. 2001;3:60 – 63. 11. Leibson CL, Katusic SK, Barbaresi WJ, et al. Use and costs of medical care for children and adolescents with and without attention-deficit/hyperactivity disorder. JAMA.2001;285:60 – 66. 12. Woodward LJ, Fergusson DM, Horwood LJ. Driving outcomes of young people with attentional difficulties in adolescence. J Am Acad Child Adolesc Psychiatr. 2000;39:627– 634. 13. DiScala C, Lescohier I, Barthel M, Li G. Injuries to children with attention deficit hyperactivity disorder. Pediatrics. 1998;102:1415–1421. 14. Cox DJ, Humphrey JW, Merkel L, et al. Controlled-release methylphenidate improves attention during on-road driving by adolescents with attention-deficit/hyperactivity disorder. J Am Board Fam Pract. 2004;17:235–239. 15. Cox DJ, Merkel RL, Kovatchev B, Seward R. Effect of stimulant medication on driving performance of young adults with attentiondeficit hyperactivity disorder: a preliminary double-blind placebo controlled trial. J Nerv Ment Dis. 2001;189:63– 64. 16. Jensen PS, Hinshaw SP, Swanson JM, et al. Findings from the

21.

22. 23.

24. 25. 26.

27.

28. 29. 30.

31. 32. 33.

34.

35.

36. 37.

38.

53

NIMH Multimodal Treatment Study of AD/HD (MTA): implications and applications for primary care providers. J Dev Behav Pediatr. 2001;22:60 –73. http://www.intelihealth.com/IH/ihtIH/WSIHW000/8271/8014/ 382756.html. Accessed May 17, 2004. Leibson CL, Long KH. Economic implications of attention-deficit hyperactivity disorder for healthcare systems. Pharmacoeconomics. 2003;21:1239 – 62. Katusic SK, Barbaresi WJ, Colligan RC, et al. Case definition in epidemiologic studies of AD/HD. Ann Epidemiol. 2005;15:430 – 437. Barbaresi W, Katusic SK, Colligan RC, et al. How common is attention-deficit/hyperactivity disorder? Incidence in a population-based birth cohort in Rochester, Minn. Arch Pediatr Adolesc Med. 2002;156:217–224. Katusic SK, Barbaresi WJ, Colligan RC, Weaver AL, Leibson CL, Jacobsen SJ. The impact of psychostimulant treatment on substance abuse among children with ADHD: a population-based, birth cohort study. J Child Adolesc Psychopharmacol. 2005;15:764 –776. Melton LJ III. History of the Rochester Epidemiology Project. Mayo Clin Proc. 1996;71:266 –274. Wagner JL, Alberts SR, Sloan JA, et al. Incremental costs of enrolling cancer patients in clinical trails: a population-based study. J Natl Cancer Inst. 1999;91:847– 853. http://www.apc-solutions.net/fedregs/000801fd.htm. Accessed March 20, 2005. http://data.bls.gov/PDQ/outside.jsp?survey⫽cu. Accessed March 20, 2005. Katusic SK, Colligan RC, Barbaresi WJ, et al. Potential influence of migration bias in birth cohort studies. Mayo Clin Proc. 1998;73:1053–1061. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994. Melton LJ III. The threat to medical records research. N Engl J Med. 1997;337:1466 –1470. Drug Topics Red Book. Montvale, NJ: Medical Economics Co. Inc.; 2000. Barbaresi WJ, Katusic SK, Colligan RC, et al. Co-morbidities among children with AD/HD: perspectives from a population-based study. Pediatr Res. 2004(April);55:1A. Liang K-Y, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika. 1986;73:13–22. Noether GE. Sample size determination for some common nonparametric tests. JASA. 1987;82:645– 647. Wolraich ML, Hannah JN, Pinnock TY, et al. Comparison of diagnostic criteria for attention-deficit hyperactivity disorder in a countywide sample. J Am Acad Child Adolesc Psychiatry. 1996;35:319 –324. Baumgartel A, Wolraich ML, Dietrich M. Comparison of diagnostic criteria for attention deficit disorders in a German elementary school sample. J Am Acad Child Adolesc Psychiatry. 1994;34:629 – 638. Pelham WE, Gnagy EM, Greenslade KE, Milich R. Teacher ratings of DSM-III-R symptoms for the disruptive behavior disorders. J Am Acad Child Adolesc Psychiatry. 1992;31:210 –218. Szatmari P, Offord DR, Boyle MH. Ontario Child Health Study. J Child Psychol Psychiatry. 1989;30:219 –230. Guevara J, Lozano P, Wickizer T, et al. Psychotropic medication use in a population of children who have attention-deficit/hyperactivity disorder. Pediatrics. 2002;109:733–739. Angold A, Erkanli A, Egger HL, Costello EJ. Stimulant treatment for children: a community perspective. Am J Child Adolesc Psychiatry. 2000;39:975–984.